Dryness stress weakens the sustainability of global vegetation cooling

Dryness stress can limit vegetation growth, and the cooling potential of vegetation will also be strongly influenced. However, it is still unclear how dryness stress feedback weakens the sustainability of vegetation-based cooling. Based on the long-time series of multi-source remote sensing product data for the period 2001-2020, the relative contribution rate, and the method of decoupling and boxing, we determined that greening will likely mitigate global warming by 0.065 ± 0.009 °C/a, but nearly 47 % of the area is unsustainable. This phenomenon is strongly related to dryness stress. The restricted area of soil moisture (SM: 68.35 %) to vegetation is larger than that of the atmospheric vapor pressure deficit (VPD: 34.19 %). With the decrease in SM, vegetation will decrease by an average of 14.9 %, and with the increase in VPD, vegetation will decrease by 3.8 %. With the continuous increase in the dryness stress area, the sustainability of the vegetation cooling effect will be threatened in an area of about 21.03 million km2, which is equivalent to the area of North America. Specifically, we found that with the decrease in SM and the increase in VPD, the contribution of vegetation to the cooling effect has been weakened by 10.8 %. This conclusion confirms that dryness stress will threaten the sustainability of vegetation-based climate cooling and provides further insight into the effect of dryness stress on vegetation cooling.

Discriminating the impacts of vegetation greening and climate change on the changes in evapotranspiration and transpiration fraction over the Yellow River Basin

Evapotranspiration (ET) is a vital parameter in terrestrial water-energy cycles. The transpiration fraction (TF) is defined as the ratio of transpiration (T) to evapotranspiration (ET), representing the contribution rate of vegetation transpiration to ecosystem ET. Quantifying the relative contributions of vegetation and climate change on the ET and TF dynamic is of great significance to better understand the water budget between the land and atmosphere. Here, we chose Yellow River Basin (YRB) as the study area and analyzed the spatiotemporal changes of ET, T, and TF from 1982 to 2015 using the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model. Meanwhile, the relative contributions of vegetation and climate change to ET, T and TF change were quantified. Model evaluation showed that the PT-JPL model performs well in the simulation of ET and T. During 1982-2015, the average annual ET, T, and TF increased at a rate of 3.20 mm/a, 0.77 mm/a and 0.003/a over the YRB during 1982-2015, respectively. The regions with significant increases in ET, T and TF almost covered the whole study area except for the upper reaches of the YRB. Vegetation greening was the main factor for the increase of ET and TF in the YRB and enhanced ET and TF at a rate of 0.72 mm/a and 0.57/a, respectively, which mainly observed in the entire Loess Plateau region (over 50 % of the study area). Precipitation (PRE) was also the dominated factor contributing to the increase in ET and TF, and temperature (TEM) showed a positive correlation with the changes in ET and TF in the most areas of YRB, which jointly dominated ET changes in the upper reaches of the YRB and TF changes in the southern part of the basin. Except for the total effects, leaf area index (LAI) also indirectly promoted ET changes by affecting PRE, TEM and relative humidity (RH). While wind speed (WS) and radiation (RAD) had a relatively weak regulatory effect on the changes in ET and TF. These findings were helpful for regional water resources management and formulating water resources-sustainable vegetation restoration strategies for local government.

Shifts bidirectional dependency between vegetation greening and soil moisture over the past four decades in China

Soil moisture (SM) has changed significantly over the past 40 years in China, while NDVI has varied dramatically, leading to increasing regional conflict between vegetation growth and water resource use. Quantifying the bidirectional dependency between SM and NDVI is essential for understanding the balance between land vegetation and water resources. However, few studies have reported their mutual feedback and spatiotemporal bidirectional dependency. This paper aims to reveal the bidirectional dependency between SM and NDVI using Granger causality test to show spatiotemporal tendency coupling patterns through trend coupling analysis, wavelet transform, and lag correlation. The Results indicated that a coupling relationship existed between SM and NDVI over most of China. The unidirectional Granger effect between SM on NDVI was 58 %, the unidirectional Granger effect of NDVI on SM was 26 %, and the bidirectional Granger relationship between SM and NDVI was 16 %. The Granger relationship is different for different soil layers or land cover types. SM and NDVI increased together in 36 % of the land cover areas, but SM increased and NDVI decreased in 12 %, and the SM decreased and NDVI increased in 27 %. The trend coupling between SM and NDVI has spatial heterogeneity. There is no change rule of coupling relationship with drought variation, but SM and NDVI increased together with more overlapping ecological restoration projects. SM decreased with the increase of NDVI from 1982 to 2010 but has reversed since 2011. NDVI and SM co-increased significantly with the implementation of ecological restoration projects during 2011-2022. The coupling relationship has a time lag effect of 1-3 months, and the time lag of NDVI to SM of deep soil layers mainly occurred in Southern China. This study illustrated the coupling framework and feedback analysis between SM and vegetation greening, which is helpful for the scientific implementing ecological restoration projects and the management of ecosystem carbon and water cycles.

Future climate imposes pressure on vulnerable ecological regions in China

Ecological regions of medium fragility account for 55 % of China's land. Large-scale afforestation and land reclamation have been carried out in these areas over the past few decades. However, how future climate change poses risks and challenges to them remains unclear. By establishing a multi-algorithm framework combining machine learning algorithms with multi-source dataset, our work predicts Normalized Difference Vegetation Index (NDVI, a proxy for vegetation greenness) and its variations in the 21st century under different climate scenarios. We find that vegetation greening (i.e., NDVI increase) in northern and southwestern China is unstable over four 20-year periods from 2020 to 2100. However, a strikingly prominent greening is expected to occur on the Qinghai-Tibet Plateau until the end of this century. Future warming can not only exacerbate the difficulties of vegetation conservation and restoration in vulnerable ecological regions, also threaten these new croplands, stymieing ambitions to increase crop production in China. Our results underscore the crucible that a warming climate presents to current restoration projects. We highlight the urgency of adapting to climate change to achieve ambitious goals of carbon sequestration and food security in China.

Grassland greening impacts on global land surface temperature

Grassland vegetation greenness has been increasing globally during the past decades. Although the vegetation coverage change could have significant effects on climate by affecting albedo and evapotranspiration (ET), the effects of global grassland greening on climate remain unclear due to the lack of long-term field observation data. Here, we used satellite measurements of land surface temperature (LST) from high coverage grassland and adjacent low coverage grassland (divided according to the leaf area index) to quantify, for the first time, the biogeophysical effects of global grassland greening on surface temperatures. Results showed that grassland greening decreased the annual mean LST and daytime LST (LSTD), but did not significantly change nighttime LST (LSTN) globally from 2003 to 2017. Spatially, grassland greening had significant cooling effects on the annual mean LST and LSTD for latitudes south of 50°N due to the cooling effect of increased ET, whereas warming affects on the annual mean LST and LSTD in the high northern latitudes (> 50°N) because of the warming effects of decreased albedo. This study revealed that the effects of grassland greening on surface temperatures changed with latitude. During June, July, and August (JJA), the increasing grassland vegetation coverage decreased the LST between 25°S and 50°N, but increased the mean LST in high northern latitudes. By contrast, grassland greening has no significant effect on the mean LST in the temperate southern hemisphere (> 25°S) during JJA due to cooling and warming effects on LSTD and LSTN, respectively. During December, January, and February, grassland greening decreased the mean LST and LSTD for latitudes south of 25°N, but increased the mean LST and LSTN for latitudes north of 25°N. This study highlights the importance of including grassland vegetation coverage in models of regional surface temperature dynamics and future climate forecast.

The contribution of forest and grassland change was greater than that of cropland in human-induced vegetation greening in China, especially in regions with high climate variability

Vegetation growth is strongly affected by both human activities and climate change. The contribution of land use change caused by human activities to vegetation growth may correlate with climate change, whereas climate variability has often been overlooked. To quantify vegetation growth during 1982-2017 in China, we used the Leaf Area Index (LAI). We also introduced climate variability to divide climate regimes using assignment entropy and built a relative greening performance indicator to identify the contribution of land use (forest, grassland, and cropland) changes to vegetation growth. The results showed that climate variability increased based on precipitation classification, and the regions with low and high climate variability accounted for 33.38%-34.41% and 12.18%-32.38% of China before and after 2000, respectively. Areas of vegetation growth affected by human activities accounted for 7.71%-19.31% and were located mainly in low variability regimes. The contribution of forest and grassland change was greater than that of cropland to vegetation greening in China, especially in high variability regimes. However, the contribution of cropland change was greater than that of forest and grassland in low variability regimes. These results imply the importance of forest and grassland change in human-induced vegetation greening, and this information can provide guidance for regional ecosystem management.

Complex anthropogenic interaction on vegetation greening in the Chinese Loess Plateau

Vegetation greening steered by land use management in the Chinese Loess Plateau has been widely reported, however studies that quantitatively assessing and explicitly linking the anthropogenic forcing on vegetation greening and browning are scarce. Here in this study, we calculate the increment and rate of change of fractional vegetation cover (FVC) from 1998 to 2018 in the Loess Plateau, and compare the results with changing rainfall, soil types, and Gross Domestic Product (GDP), to detail a systematic assessment of the role of the climate-vegetation-human nexus. We have observed that nearly 80% of the study area has undergone greening, and noticed that rainfall was not the main driver of rapid vegetation change, instead of human land use management such as, irrigation along the Yellow River, snowmelt-runoff irrigation, and irrigation from reservoirs formed by check dams contributed the most for the increased FVC in the Chinese Loess Plateau. Concurrently, rapid vegetation browning is almost fully driven by urban expansion. Our findings show that GDP growth promotes both browning and greening, indicative of sustainable development in the Loess plateau region. These contrasting trends reveal that the relationship between human activities and greening is very complex.

The role of climate change and vegetation greening on the variation of terrestrial evapotranspiration in northwest China's Qilian Mountains

Terrestrial evapotranspiration (ET_a) reflects the complex interactions of climate, vegetation, soil and terrain and is a critical component in water and energy cycles. However, the manner in which climate change and vegetation greening influence ET_a remains poorly understood, especially in alpine regions. Drawing on the Global Land Evaporation Amsterdam Model (GLEAM) ET_a data, the interannual variability of ET_a and its ties to precipitation (P), potential evaporation (ET_p) and vegetation (NDVI) were analysed. The Budyko framework was implemented over the period of 1982 to 2015 to quantify the response of ET_a to climate change's direct (P and ET_p) and indirect (NDVI) impacts. The ET_a, P, ET_p and NDVI all showed significant increasing trends from 1981 to 2015 with rates of 1.52 mm yr^-1, 3.18 mm yr^-1, 0.89 mm yr^-1 and 4.0 × 10^-4 yr^-1, respectively. At the regional level, the positive contribution of increases in P and NDVI offset the negative contribution of ET_p to the change in ET_a (∆ET_a). The positive ∆ET_a between 1982 and 2001 was strongly linked with the concomitant increase in NDVI. Increases in vegetation contributing to a positive ∆ET_a differed among landscape types: for shrub, meadow and steppe they occurred during both periods, for alpine vegetation between 1982 and 2001, and for desert between 2002 and 2015. Climate change directly contributed to a rise in ET_a, with P as the dominant factor affecting forested lands during both periods, and alpine vegetation between 2002 and 2015. Moreover, ET_p was a dominant factor for the desert between 1982 and 2001, where the variation of P was not significant. The contributions of factors having an impact on ∆ET_a are modulated by both the sensitivity of impact factors acting on ET_a as well as the magnitudes of factor changes. The greening of vegetation can influence ET_a by increasing vegetation transpiration and rainfall interception in forest, brush and meadow landscapes. These findings can help in developing a better understanding of the interaction of ecosystems and hydrology in alpine regions.

Prominent vegetation greening and its correlation with climatic variables in northern China

Global vegetation has been reported to be turning greener, especially in China and India. The Yellow River Basin is one of the most prominent greening areas in China. While some studies have attributed vegetation greening to large-scale ecological restoration efforts, our study focuses on the role of climate change in vegetation greening. We selected a time series of annual vegetation net primary productivity (NPP) and vegetation coverage from satellite data to quantify the vegetation greening trend. Annual temperature and precipitation were selected to examine the climate trend from 2000 to 2019. The results showed that the Yellow River Basin experienced a rapid increase in temperature and precipitation during this period. Annual temperature increased with an average speed of 0.905 °C per decade, approximately 4.5 times larger than that of global warming. Annual precipitation increased by 82.8%, with an average speed of 9.17 mm per year. There was widespread vegetation greening in the Yellow River Basin during 2000-2019. This was demonstrated by an increase in vegetation NPP and vegetation coverage in the Yellow River Basin. The increase of annual NPP and coverage from 2000 to 1019 was 26.6% and 30.8%, respectively. Even while considering the effects of conservation and restoration efforts, the rapid increases in temperature and precipitation allowed vegetation to flourish, as evidenced by significant positive correlations between climate variables and vegetation variables. Therefore, climate change played an important positive role in vegetation greening, rather than an undesirable disturbance.

Pattern of NDVI-based vegetation greening along an altitudinal gradient in the eastern Himalayas and its response to global warming

The eastern Himalayas, especially the Yarlung Zangbo Grand Canyon Nature Reserve (YNR), is a global hotspot of biodiversity because of a wide variety of climatic conditions and elevations ranging from 500 to > 7000 m above sea level (a.s.l.). The mountain ecosystems at different elevations are vulnerable to climate change; however, there has been little research into the patterns of vegetation greening and their response to global warming. The objective of this paper is to examine the pattern of vegetation greening in different altitudinal zones in the YNR and its relationship with vegetation types and climatic factors. Specifically, the inter-annual change of the normalized difference vegetation index (NDVI) and its variation along altitudinal gradient between 1999 and 2013 was investigated using SPOT-VGT NDVI data and ASTER global digital elevation model (GDEM) data. We found that annual NDVI increased by 17.58% in the YNR from 1999 to 2013, especially in regions dominated by broad-leaved and coniferous forests at lower elevations. The vegetation greening rate decreased significantly as elevation increased, with a threshold elevation of approximately 3000 m. Rising temperature played a dominant role in driving the increase in NDVI, while precipitation has no statistical relationship with changes in NDVI in this region. This study provides useful information to develop an integrated management and conservation plan for climate change adaptation and promote biodiversity conservation in the YNR.